1. A system for repositioning teeth from an initial tooth arrangement to a final tooth arrangement, said system comprising a plurality of incremental position adjustment appliances comprising shells having cavities shaped to receive and reposition teeth, which appliances are successively worn by a patient to move teeth from one arrangement to a successive arrangement, wherein at least one of the appliances is a multi-layer shell appliance shaped to receive only upper arch teeth or lower arch teeth of the patient, the multi-layer shell appliance comprising a first polymeric material having a molecular structure which provides a first elastic modulus and the same appliance further comprising a second polymeric material of a different type having a molecular structure which provides a second elastic modulus, and wherein at least one of the appliances comprises a shell having a different geometry than that of at least one other appliance in the system, and wherein at least two different appliances of the system have different elastic moduluses and hardnesses with respect to each other, and wherein the first elastic modulus and the second elastic modulus each have a stiffness sufficient to impart a tooth moving force when the multi-layer shell appliance is worn by the patient.
2. A system as in claim 1, wherein the plurality of appliance further comprises:
an additional first appliance consisting entirely of the first material; and
an additional second appliance consisting entirely of the second material.
3. A system as in claim 2, further comprising:
an additional third appliance consisting entirely of a third material.
4. A system as in claim 2, further comprising:
an additional third appliance consisting entirely of either the first or second material.
5. A system as in claim 2, wherein the first material has an elastic modulus that is less than an elastic modulus of the second material.
6. A system as in claim 2, wherein the first material has an elastic modulus that is greater than an elastic modulus of the second material.
7. A system as in claim 2, wherein the additional first and second appliances have the same geometry.
8. A system as in claim 2, wherein the additional first and second appliances have different geometries.
9. A method for moving one or more of a patient’s teeth, the method comprising:
providing a first appliance for placement in the patient’s mouth;
providing a second appliance for subsequent placement in the patient’s mouth in place of the first appliance; and
providing a third appliance for subsequent placement in the patient’s mouth in place of the second appliance,
wherein at least one of the first, second and third appliances is a multi-layer shell appliance shaped to receive only upper arch teeth or lower arch teeth of the patient and further comprises a first polymeric material having a molecular structure which provides a first elastic modulus and the same appliance further comprising a second polymeric material having a molecular structure which provides a second elastic modulus that is different from the first elastic modulus, and
wherein each of the appliances comprise teeth receiving cavities shaped to receive and resiliently position the patient’s teeth and wherein at least one of the first, second and third appliances has teeth receiving cavities having a geometry that differs from a geometry of the teeth receiving cavities of one of the other appliances,
wherein each of the appliances is designed prior to providing the first appliance for placement in the patient’s mouth, and wherein the first elastic modulus and the second elastic modulus each have a stiffness sufficient to impart a tooth moving force when the multi-layer shell appliance is worn by the patient.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method for object recognition of a three dimensional (3D) object, comprising the steps of:
obtaining at least one two dimensional (2D) representation of said object;
detecting image features in said obtained 2D representation;
recovering a highly probable 3D shape of said object of a certain object class consistent with 2D images of said object using at least one obtained image where 2D features are detected and using a learned statistical multi-view shape model of the shape variation; and
comparing said recovered 3D shape with a reference representation of at least one object of said object class.
2. The method according to claim 1, wherein said recovered 3D shape is a complete surface model.
3. The method according to claim 2, wherein said complete surface model is inferred from 2D or 3D features.
4. The method according to claim 1, wherein said object class contains non-rigid objects and said statistical shape model is learned using 2D and 3D data specific for possible deformations of the objects in said non-rigid object class.
5. The method according to claim 1, further comprising the step of identifying an individual object of an object class or aiding in the identification of an individual object using said recovered 3D shape.
6. The method according to claim 1, further comprising the step of verifying the identity of an individual object of an object class or aiding in the verification of the identity of an individual object using said recovered 3D shape.
7. The method according to claim 2, further comprising the step of: fitting a surface to said recovered 3D shape using a learned statistical shape model for said surface of the object in order to regularize said surface shape in a manner specific for said object class.
8. The method according to claim 1, wherein said object may be one or several of: a human face, a human body, inner organ(s) of a human body, blood vessel, animal, inner organs of an animal, a tumor, manufactured product(s) from an industrial process, a vehicle, an aircraft, a ship, military object(s).
9. The method according to claim 1, wherein said reference representation is stored in at least one of a non-volatile memory, database server, and personal identification card.
10. A device for object recognition of a three dimensional (3D) object, comprising:
means for obtaining at least one two dimensional (2D) representation of said object;
means for detecting image features in said obtained 2D representation;
means for recovering a highly probable 3D shape of said object of a certain object class consistent with 2D images of said object using one or more images where 2D features are detected and using a learned statistical multi-view shape model of the shape variation; and
means for comparing said recovered 3D shape with a reference representation of at least one object of said object class.
11. The device according to claim 10, wherein said recovered 3D shape is a complete surface model.
12. The device according to claim 11, wherein said complete surface model is inferred from 2D or 3D features.
13. The device according to claim 10, wherein said object class contains non-rigid objects and said statistical shape model is learned using 2D and 3D data specific for possible deformations of the objects in said non-rigid object class.
14. The device according to claim 10 further comprising means for identifying an individual object of an object class or aiding in the identification of an individual object using said recovered 3D shape.
15. The device according to claim 10, further comprising means for verifying the identity of an individual object of an object class or aiding in the verification of the identity of an individual object using said recovered 3D shape.
16. The device according to claim 11, further comprising means for: fitting a surface to said recovered 3D shape using a learned statistical shape model for said surface of the object in order to regularize said surface shape in a manner specific for said object class.
17. The device according to claim 10, wherein said object may be one or several of: a human face, a human body, inner organ(s) of a human body, blood vessel, animal, inner organs of an animal, a tumor, manufactured product(s) from an industrial process, a vehicle, an aircraft, a ship, military object(s).
18. The device according to claim 17, wherein said recovered 3D shapes of blood vessels or organs recovered from 2D projections, e.g. using X-ray imaging, are used for navigating steerable catheters or aiding physicians by displaying said recovered 3D shape.
19. The device according to claim 17, wherein said recovered 3D shapes of facial features are used to identify or to verify an identity of an individual in an access control system or security system, resulting in an acceptance or rejection of said individual.
20. The device according to claim 10, further comprising an interface for communicating with a personal identification card wherein said reference representation is stored.
21. A computer program stored in a computer readable storage medium and executed in a computational unit for object recognition of a three dimensional (3D) object, comprising:
an instruction set for obtaining at least one externally acquired two dimensional (2D) representation of said 3D object;
an instruction set for detecting image features in said obtained 2D representation;
an instruction set for recovering a highly probable 3D shape of said 3D object of a certain object class consistent with 2D images of said 3D object using one or more images where 2D features are detected and using a learned statistical multi-view shape model of the shape variation; and
an instruction set for comparing said recovered 3D shape with a reference representation of at least one object of said object class;
22. The computer program according to claim 21, further comprising an instruction set for identifying andor verifying an individual object of an object class or aiding in said identification andor verification of said individual object using said recovered 3D shape.
23. A system for object recognition of a three dimensional (3D) object, comprising:
means for obtaining at least one two dimensional (2D) representation of said 3D object;
means for detecting image features in said obtained 2D representation;
means for recovering a highly probable 3D shape of said 3D object of a certain object class consistent with 2D images of said 3D object using one or more images where 2D features are detected and using a learned statistical multi-view shape model of the shape variation;
means for comparing said recovered 3D shape with a reference representation of at least one object of said object class; and
means for responding to a result from said means for comparison.
24. The system according to claim 23, further comprising means for identifying andor verifying an individual object of an object class or aiding in said identification andor verification of said individual object using said recovered 3D shape.
25. The system according to claim 23, wherein said reference representation is stored in at least one of a non-volatile memory, database server, and personal identification card.